We are going to use K-means algorithm to cluster 6 data points from dataset D = {0, 1, 2, 3, 4, 2022} in R1 into 2 clusters. Before the first iteration, the cluster centers are randomly initialized at c1 = 0.235 and c2 = 1.984. Next, we simulate the first iteration (for part (a) and (b)) of K-means with manual computation. (a) Compute the cluster assignment for each of the 6
We are going to use K-means algorithm to cluster 6 data points from dataset D = {0, 1, 2, 3, 4, 2022} in R1 into 2 clusters. Before the first iteration, the cluster centers are randomly initialized at c1 = 0.235 and c2 = 1.984. Next, we simulate the first iteration (for part (a) and (b)) of K-means with manual computation. (a) Compute the cluster assignment for each of the 6
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We are going to use K-means algorithm to cluster 6 data points from dataset D = {0, 1, 2, 3, 4, 2022} in R1 into 2 clusters. Before the first iteration, the cluster centers are randomly initialized at c1 = 0.235 and c2 = 1.984. Next, we simulate the first iteration (for part (a) and (b)) of K-means with manual computation.
(a) Compute the cluster assignment for each of the 6 data points given, using the Euclidean distance. [5 pts]
(b) Compute the updated cluster center c1 and c2. [5 pts]
(c) How many iterations are needed to finish the K-means algorithm for this problem? [10 pts]
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